Vision AI Pose Paper Prototype

@Muhammadzeesha59

With a decade of experience in MT4 and MT5 platforms, I am well versed in working with complex algorithms and ensuring high accuracy in resulting data. Your project of creating a paper prototype that can convert textual cues to pose outputs seems like an exciting challenge that I would love to take on. The skills I have acquired throughout the years, including coding trading platforms and using Pine scripts and Quant Trading System, have trained me to deliver efficient and predictable solutions which are essential in reproducing the chain of work we need. I am confident that my expertise will help me create a functional LLM prompt template and parsing code, ensuring great precision in extracting joint actions from textual inputs. Additionally, being skilled in OpenAI and Hugging Face tools puts me in an advantageous position to manipulate Long Language Models just as required by your project's needs in terms of understanding instructions and generating relevant outcomes. In summary, my skills and experience as a skilled Full-Stack Developer, particularly my proficiency with OpenAI, Hugging Face tools, Java Python , Quant Trading System, Deep Learning , Machiene Learning , AWS Lambda aligns very well with the requirements of your Vision AI Pose Paper Prototype project. Choose me for optimal results within a reasonable budget. Let's discuss further on how I can exceed your expectations for this sprint!

@sajjadtaghvaeifr

Hello, I trust you're doing well. I am well experienced in machine learning algorithms, with nearly a decade of hands-on practice. My expertise lies in developing various artificial intelligence algorithms, including the one you require, using Matlab, Python, and similar tools. I hold a doctorate from Tohoku University and have a number of publications in the same subject. My portfolio, which showcases my past work, is available for your review. Your project piqued my interest, and I would be delighted to be part of it. Let's connect to discuss in detail. Warm regards. please check my portfolio link: https://www.freelancer.com/u/sajjadtaghvaeifr

@manoval09

Hi, You need a fast proof-of-concept that validates whether textual instructions can drive pose logic — the kind of throwaway prototype where the idea matters more than the code quality. I'd wire this up with MediaPipe Pose for skeleton extraction and use a lightweight instruction parser (spaCy or even regex-first for speed) to map text commands like "raise left arm to 90 degrees" to joint angle targets. The key architectural decision is keeping the vision pipeline and instruction interpreter decoupled so you can swap either side without rebuilding the whole thing. A Jupyter notebook makes the most sense here — visual outputs inline, easy to demo, no deployment overhead. In the first 24 hours I'd have a working loop: camera feed → pose landmarks → text instruction → angle delta comparison, with a simple pass/fail overlay showing whether the pose matches the instruction. Before I start: is the textual input free-form natural language, or a defined command syntax? That changes whether spaCy's dependency parser earns its weight or whether regex is the right call at this scope. Best regards, Val

@demivision

With over 20 years of technical experience, especially in the domain of AI and computer vision, I would be an ideal fit for your project. My team at DemiVision has a proven track record of delivering reliable and scalable solutions, as we build with the future in mind. We understand that this stage is about proving the concept rather than a polished UI and we are more than capable of delivering on that. We not only have extensive experience with LLM prompt engineering and developing AI integrations but also have a deep understanding of the core technologies you have mentioned, like OpenAI, Hugging Face, and Three.js. Having developed cutting-edge applications using these technologies in the past, we can confidently assure you that our implementation not only will be transparent and reproducible but also well-documented for seamless extensibility. But most importantly, we value building long-term relationships with our clients. By choosing us, you're not just hiring a freelancer, you're gaining a committed technology partner dedicated to ensuring your project's success from initial strategy and development all the way to ongoing optimization. We look forward to embarking on this sprint with you and demonstrating how textual cues can be transformed into accurate anatomical motions to revolutionize your biomechanical workflow.

@GenoraLabs

Hello, I'm intrigued by your project and have a few questions to better understand your vision. Have you already identified the specific LLM and Vision AI tools you plan to use for this prototype? I would recommend considering tools like OpenAI, Hugging Face, or Mediapipe for seamless integration. I propose to handle your Vision AI Pose Paper Prototype project by creating a functional paper prototype that showcases the workflow from textual cues to accurate anatomical motion visualization. I will focus on developing a clear LLM prompt template, parsing code for extracting joint actions, and implementing a minimal visual preview to confirm the biomechanical plausibility of the poses. Core Deliverables: - A runnable or shareable prototype demonstrating the pipeline from textual cue to pose output - LLM prompt template and parsing code for joint actions extraction - Minimal visual preview driven by generated pose data - Short read-me documentation outlining assumptions, libraries used, and instructions for extending the prototype I'll share my portfolio with you in the DM. Kindly ping me there. My experience with LLM parsing and Vision AI tools ensures quality, consistency, and a smooth delivery. I'd be happy to discuss your project further and answer any questions. Best regards,

@Werollsol

With my experience in AI and automation, I believe I'm the perfect candidate for your Vision AI Pose Prototype project. One of my core competencies is developing API integrations and workflows using Python. This skillset aligns perfectly with the task at hand, where the textual instructions need to be fed into an LLM before they're parsed and turned into joint-level positions. In terms of interpretability and creating transparency, I am well-versed with using familiar tools such as OpenAI, Hugging Face and Mediapipe in my work. Additionally, my understanding of data pipelines will ensure that your prototype remains extensible and can be scaled up to full production mode seamlessly. Moreover, my ability to explain complex technical concepts in a way that's easily understood by everyone will serve us well during the project's documentation phase. I’m confident that I can create a prototype that not only meets your expectations but also provides a solid foundation for developing the end-to-end workflow you envision. Let's embark on this enjoyable sprint together!

@markupdudes

Hi there, I’m excited about your Vision AI Pose Paper Prototype, it’s a brilliant concept to bridge textual instructions with biomechanically accurate motion using LLMs and lightweight vision AI. I have solid experience in LLM prompt engineering and developing rapid prototypes that connect natural language inputs to precise outputs, alongside practical computer vision skills using tools like Mediapipe and Three.js. I'll craft a streamlined pipeline that parses your cues, outputs joint-level data, and visualizes poses as easy-to-verify stick figures, ensuring every step is transparent and extendable. For deliverables, expect a clean Jupyter notebook demo reflecting your sample cues, the parsing logic, stick-figure previews, and a concise read-me outlining assumptions and next steps. I propose to deliver this within 7 days to provide quick validation while allowing room for iterations. Which five sample cues would you like me to start with for validating the prototype? Best regards,

@shadabkhan92

As an AI specialist with a strong background in agentic AI and LLM integration, I understand the nuances and challenges involved in building sophisticated systems like the one you envision for your project. My team and I have extensive experience bringing transformative AI capabilities into various industries via different deployment platforms such as web, mobile, and IoT devices. Thus, we are well-equipped to deliver a robust, end-to-end solution that combines both LLM parsing and visual preview - showcasing accurate joint action extraction and plausible anatomical motions. What truly differentiates us is our ability to operate on the bleeding edge of technology without sacrificing practicality. We've successfully deployed models utilizing OpenAI, Hugging Face, TensorFlow, PyTorch alike – ensuring the stack our customers rely on meets their specific needs. Furthermore, we deeply understand the criticality of detailed documentation; hence our deliveries will be accompanied by comprehensive read-me explaining libraries used, assumptions made, and how to extend the prototype into full production.

@qaiserkhan0318

Hello, I’m interested in building this text-to-pose prototype. With my background in AI, computer vision, and deep learning, I can design a clean and transparent pipeline that converts structured textual instructions into joint-level pose data and visualizes it as a stick-figure preview. I have experience working with LLMs, Python, PyTorch, OpenCV, and vision-based systems, and I can quickly build a lightweight notebook or runnable demo that demonstrates: Text → LLM parsing → Joint coordinates → Minimal 2D/3D visualization, along with clear documentation for extending it into a full production system. I focus on practical, reproducible prototypes that clearly prove the concept while keeping the architecture simple and scalable. Looking forward to collaborating

@viktork64

As a Full Stack | AI Developer with extensive experience, I’m confident I can deliver an excellent solution for your Vision AI Pose Paper Prototype project. My expertise spans from front-end design to end-to-end system development, including intelligent features like the one you're seeking. I've also worked on integrating LLM prompts and assembling quick Vision AI hacks, making this project well-aligned with my skill set. One of my key strengths is in developing clean, maintainable code that allows for transparent and reproducible workflows - something immensely valuable for your project. Moreover, I regularly work with popular AI tools such as OpenAI and Hugging Face, which can further enhance the efficacy of our collaboration. By leveraging my skillset and experience, I assure you I can deliver a functional prototype that translates textual cues into accurate poses within the provided tolerance. I value clear communication and timely delivery of projects, attributes that have earned me a reputation for quality deliverables. With my passion for tinkering with new technologies and endless curiosity, I'm confident working on your project will be a stimulating sprint into the potentiality of LLM parsing and Vision AI in pose evaluation. Let's discuss further; together we can turn your idea into an impressive reality!